基于宽度学习系统的轨道交通车辆噪声电流测试方法  

Noise Currents Measurement Method for Rail Vehicles Based on Broad Learning System

作　　者：韩冉 李杰 练成 张坤 HAN Ran;LI Jie;LIAN Cheng;ZHANG Kun(CRRC Nanjing Puzhen Co.,Ltd.,Nanjing,Jiangsu 210000,China)

机构地区：[1]中车南京浦镇车辆有限公司,江苏南京210000

出　　处：《控制与信息技术》2023年第4期10-17,共8页CONTROL AND INFORMATION TECHNOLOGY

摘　　要：为保证列车与轨旁通信系统的电磁兼容性,国内外地铁项目对列车在运营过程中产生的噪声电流都有严格的限值要求。目前地铁车辆噪声电流测试普遍采用电流传感器加滤波器的方法,该方法增加了设备安装数量,而且设备不易携带且搬运过程中容易损坏。为了提高试验效率,降低试验成本,文章提出一种基于宽度学习系统(BLS)的车辆噪声电流测量方法。其首先将由柔性电流环和数据记录仪获取的电流数据样本进行分割,然后对分割后的样本进行傅里叶变换(FFT),最后提取频率信号作为BLS模型的输入,从而获取相应的噪声电流值。试验结果表明,基于BLS模型得到的噪声电流值平均误差在4%左右,符合试验的要求,而且该方法的测试准确率明显优于加权法、BP神经网络、粒子群优化及人工蜂群等现有方法,验证了所提测试方法的有效性。In order to ensure the electromagnetic compatibility between train and trackside communication system,metro projects at home and abroad have strict limits for the noise current generated by train during operation.At present,current sensors and filters are commonly used in the test of noise current of metro vehicles.This method increases the number of installed devices,and the device have poor portability,and are prone to damage during handling.In order to improve test efficiency and reduce costs,this paper proposes a vehicle noise current measurement method based on the broad learning system(BLS).Firstly,the current data samples obtained by flexible current loop and data recorder are divided,and then Fourier transform(FFT)is performed on the divided samples.Finally,the BLS model extracts the frequency signal as the input to obtain the corresponding noise current value.The experimental results show that the average error of the noise current value obtained by the BLS model is around 4%,which meets the experimental requirements.Moreover,the testing accuracy of this method is significantly better than existing methods:weighting method,BP neural network,particle swarm optimization and artificial bee colony,the effectiveness of the proposed testing method has been verified.

关 键 词：轨道交通 电磁兼容 车辆噪声电流 宽度学习系统 傅里叶变换 

分 类 号：TM937.4[电气工程—电力电子与电力传动]